Optimizing de novo genome assembly from PCR-amplified metagenomes

Background. Metagenomics has transformed our understanding of microbial diversity across ecosystems, with recent advances enabling de novo assembly of genomes from metagenomes. These metagenome-assembled genomes are critical to provide ecological, evolutionary, and metabolic context for all the microbes and viruses yet to be cultivated. Metagenomes can now be generated from nanogram to subnanogram amounts of DNA. However, these libraries require several rounds of PCR amplification before sequencing, and recent data suggest these typically yield smaller and more fragmented assemblies than regular metagenomes. Methods. Here we evaluate de novo assembly methods of 169 PCR-amplified metagenomes, including 25 for which an unamplified counterpart is available, to optimize specific assembly approaches for PCR-amplified libraries. We first evaluated coverage bias by mapping reads from PCR-amplified metagenomes onto reference contigs obtained from unamplified metagenomes of the same samples. Then, we compared different assembly pipelines in terms of assembly size (number of bp in contigs ≥ 10kb) and error rates to evaluate which are the best suited for PCR-amplified metagenomes. Results. Read mapping analyses revealed that the depth of coverage within individual genomes is significantly more uneven in PCR-amplified datasets versus unamplified metagenomes, with regions of high depth of coverage enriched in short inserts. This enrichment scales with the number of PCR cycles performed, and is presumably due to preferential amplification of short inserts. Standard assembly pipelines are confounded by this type of coverage unevenness, so we evaluated other assembly options to mitigate these issues. We found that a pipeline combining read deduplication and an assembly algorithm originally designed to recover genomes from libraries generated after whole genome amplification (single-cell SPAdes) frequently improved assembly of contigs ≥ 10kb by 10 to 100-fold for low input metagenomes. Conclusions. PCR-amplified metagenomes have enabled scientists to explore communities traditionally challenging to describe, including some with extremely low biomass or from which DNA is particularly difficult to extract. Here we show that a modified assembly pipeline can lead to an improved de novo genome assembly from PCR-amplified datasets, and enables a better genome recovery from low input metagenomes.

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Optimizing de novo genome assembly from PCR-amplified metagenomes

10.7287/peerj.preprints.27453v1 ◽

2018 ◽

Author(s):

Simon Roux ◽

Gareth Trubl ◽

Danielle Goudeau ◽

Nandita Nath ◽

Estelle Couradeau ◽

...

Keyword(s):

Genome Assembly ◽

De Novo Assembly ◽

De Novo ◽

Pcr Amplification ◽

Error Rates ◽

De Novo Genome Assembly ◽

Low Input ◽

Assembly Algorithm ◽

Coverage Bias ◽

Assembly Pipeline

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Optimizing de novo genome assembly from PCR-amplified metagenomes

PeerJ ◽

10.7717/peerj.6902 ◽

2019 ◽

Vol 7 ◽

pp. e6902 ◽

Cited By ~ 9

Author(s):

Simon Roux ◽

Gareth Trubl ◽

Danielle Goudeau ◽

Nandita Nath ◽

Estelle Couradeau ◽

...

Keyword(s):

Genome Assembly ◽

De Novo ◽

Pcr Amplification ◽

Error Rates ◽

De Novo Genome Assembly ◽

Low Input ◽

Assembly Algorithm ◽

Coverage Bias ◽

Size Number ◽

Assembly Pipeline

Background Metagenomics has transformed our understanding of microbial diversity across ecosystems, with recent advances enabling de novo assembly of genomes from metagenomes. These metagenome-assembled genomes are critical to provide ecological, evolutionary, and metabolic context for all the microbes and viruses yet to be cultivated. Metagenomes can now be generated from nanogram to subnanogram amounts of DNA. However, these libraries require several rounds of PCR amplification before sequencing, and recent data suggest these typically yield smaller and more fragmented assemblies than regular metagenomes. Methods Here we evaluate de novo assembly methods of 169 PCR-amplified metagenomes, including 25 for which an unamplified counterpart is available, to optimize specific assembly approaches for PCR-amplified libraries. We first evaluated coverage bias by mapping reads from PCR-amplified metagenomes onto reference contigs obtained from unamplified metagenomes of the same samples. Then, we compared different assembly pipelines in terms of assembly size (number of bp in contigs ≥ 10 kb) and error rates to evaluate which are the best suited for PCR-amplified metagenomes. Results Read mapping analyses revealed that the depth of coverage within individual genomes is significantly more uneven in PCR-amplified datasets versus unamplified metagenomes, with regions of high depth of coverage enriched in short inserts. This enrichment scales with the number of PCR cycles performed, and is presumably due to preferential amplification of short inserts. Standard assembly pipelines are confounded by this type of coverage unevenness, so we evaluated other assembly options to mitigate these issues. We found that a pipeline combining read deduplication and an assembly algorithm originally designed to recover genomes from libraries generated after whole genome amplification (single-cell SPAdes) frequently improved assembly of contigs ≥10 kb by 10 to 100-fold for low input metagenomes. Conclusions PCR-amplified metagenomes have enabled scientists to explore communities traditionally challenging to describe, including some with extremely low biomass or from which DNA is particularly difficult to extract. Here we show that a modified assembly pipeline can lead to an improved de novo genome assembly from PCR-amplified datasets, and enables a better genome recovery from low input metagenomes.

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Accurate long-read de novo assembly evaluation with Inspector

Genome Biology ◽

10.1186/s13059-021-02527-4 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Yu Chen ◽

Yixin Zhang ◽

Amy Y. Wang ◽

Min Gao ◽

Zechen Chong

Keyword(s):

Genome Assembly ◽

De Novo Assembly ◽

In Silico ◽

Large Scale ◽

De Novo ◽

Small Scale ◽

De Novo Genome Assembly ◽

Consensus Sequences ◽

Assembly Evaluation ◽

Long Read

AbstractLong-read de novo genome assembly continues to advance rapidly. However, there is a lack of effective tools to accurately evaluate the assembly results, especially for structural errors. We present Inspector, a reference-free long-read de novo assembly evaluator which faithfully reports types of errors and their precise locations. Notably, Inspector can correct the assembly errors based on consensus sequences derived from raw reads covering erroneous regions. Based on in silico and long-read assembly results from multiple long-read data and assemblers, we demonstrate that in addition to providing generic metrics, Inspector can accurately identify both large-scale and small-scale assembly errors.

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Fully phased human genome assembly without parental data using single-cell strand sequencing and long reads

Nature Biotechnology ◽

10.1038/s41587-020-0719-5 ◽

2020 ◽

Author(s):

David Porubsky ◽

◽

Peter Ebert ◽

Peter A. Audano ◽

Mitchell R. Vollger ◽

...

Keyword(s):

Single Cell ◽

Genome Assembly ◽

De Novo ◽

Error Rates ◽

Sequencing Data ◽

Single Nucleotide Variants ◽

De Novo Genome Assembly ◽

Parental Data ◽

Human Genome Assembly ◽

Long Read

AbstractHuman genomes are typically assembled as consensus sequences that lack information on parental haplotypes. Here we describe a reference-free workflow for diploid de novo genome assembly that combines the chromosome-wide phasing and scaffolding capabilities of single-cell strand sequencing1,2 with continuous long-read or high-fidelity3 sequencing data. Employing this strategy, we produced a completely phased de novo genome assembly for each haplotype of an individual of Puerto Rican descent (HG00733) in the absence of parental data. The assemblies are accurate (quality value > 40) and highly contiguous (contig N50 > 23 Mbp) with low switch error rates (0.17%), providing fully phased single-nucleotide variants, indels and structural variants. A comparison of Oxford Nanopore Technologies and Pacific Biosciences phased assemblies identified 154 regions that are preferential sites of contig breaks, irrespective of sequencing technology or phasing algorithms.

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A high-quality de novo genome assembly from a single parasitoid wasp

10.1101/2020.07.13.200725 ◽

2020 ◽

Cited By ~ 1

Author(s):

Xinhai Ye ◽

Yi Yang ◽

Zhaoyang Tian ◽

Le Xu ◽

Kaili Yu ◽

...

Keyword(s):

Genome Assembly ◽

De Novo ◽

Parasitoid Wasp ◽

Genome Comparison ◽

Single Individual ◽

High Quality ◽

De Novo Genome Assembly ◽

Low Input ◽

A Genome ◽

High Level

AbstractSequencing and assembling a genome with a single individual have several advantages, such as lower heterozygosity and easier sample preparation. However, the amount of genomic DNA of some small sized organisms might not meet the standard DNA input requirement for current sequencing pipelines. Although few studies sequenced a single small insect with about 100 ng DNA as input, it may still be challenging for many small organisms to obtain such amount of DNA from a single individual. Here, we use 20 ng DNA as input, and present a high-quality genome assembly for a single haploid male parasitoid wasp (Habrobracon hebetor) using Nanopore and Illumina. Because of the low input DNA, a whole genome amplification (WGA) method is used before sequencing. The assembled genome size is 131.6 Mb with a contig N50 of 1.63 Mb. A total of 99% Benchmarking Universal Single-Copy Orthologs are detected, suggesting the high level of completeness of the genome assembly. Genome comparison between H. hebetor and its relative Bracon brevicornis shows a high-level genome synteny, indicating the genome of H. hebetor is highly accurate and contiguous. Our study provides an example for de novo assembling a genome from ultra-low input DNA, and will be used for sequencing projects of small sized species and rare samples, haploid genomics as well as population genetics of small sized species.

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Pushing the limits of de novo genome assembly for complex prokaryotic genomes harboring very long, near identical repeats

10.1101/300186 ◽

2018 ◽

Cited By ~ 3

Author(s):

Michael Schmid ◽

Daniel Frei ◽

Andrea Patrignani ◽

Ralph Schlapbach ◽

Jürg E. Frey ◽

...

Keyword(s):

Dark Matter ◽

Genome Assembly ◽

De Novo ◽

Bacterial Genomes ◽

De Novo Genome Assembly ◽

Assembly Algorithm ◽

Long Reads ◽

Oxford Nanopore ◽

Prokaryotic Genomes ◽

Genome Assemblies

AbstractGenerating a complete, de novo genome assembly for prokaryotes is often considered a solved problem. However, we here show that Pseudomonas koreensis P19E3 harbors multiple, near identical repeat pairs up to 70 kilobase pairs in length. Beyond long repeats, the P19E3 assembly was further complicated by a shufflon region. Its complex genome could not be de novo assembled with long reads produced by Pacific Biosciences’ technology, but required very long reads from the Oxford Nanopore Technology. Another important factor for a full genomic resolution was the choice of assembly algorithm.Importantly, a repeat analysis indicated that very complex bacterial genomes represent a general phenomenon beyond Pseudomonas. Roughly 10% of 9331 complete bacterial and a handful of 293 complete archaeal genomes represented this dark matter for de novo genome assembly of prokaryotes. Several of these dark matter genome assemblies contained repeats far beyond the resolution of the sequencing technology employed and likely contain errors, other genomes were closed employing labor-intense steps like cosmid libraries, primer walking or optical mapping. Using very long sequencing reads in combination with assemblers capable of resolving long, near identical repeats will bring most prokaryotic genomes within reach of fast and complete de novo genome assembly.

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GraphSeq: Accelerating String Graph Construction for De Novo Assembly on Spark

10.1101/321729 ◽

2018 ◽

Author(s):

Chung-Tsai Su ◽

Ming-Tai Chang ◽

Yun-Chian Cheng ◽

Yun-Lung Li ◽

Yao-Ting Wang

Keyword(s):

Genome Assembly ◽

De Novo Assembly ◽

De Novo ◽

Data Representation ◽

Important Application ◽

Supplementary Information ◽

De Novo Genome Assembly ◽

String Graph ◽

Computing Framework ◽

Variant Identification

AbstractSummary: De novo genome assembly is an important application on both uncharacterized genome assembly and variant identification in a reference-unbiased way. In comparison with de Brujin graph, string graph is a lossless data representation for de novo assembly. However, string graph construction is computational intensive. We propose GraphSeq to accelerate string graph construction by leveraging the distributed computing framework.Availability and Implementation: GraphSeq is implemented with Scala on Spark and freely available at https://www.atgenomix.com/blog/graphseq.Supplementary information: Supplementary data are available at Bioinformatics online.

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De novo Nanopore read quality improvement using deep learning

BMC Bioinformatics ◽

10.1186/s12859-019-3103-z ◽

2019 ◽

Vol 20 (1) ◽

Cited By ~ 4

Author(s):

Nathan LaPierre ◽

Rob Egan ◽

Wei Wang ◽

Zhong Wang

Keyword(s):

Error Correction ◽

Genome Assembly ◽

Large Scale ◽

De Novo ◽

Error Rates ◽

De Novo Genome Assembly ◽

Sequencing Technologies ◽

Oxford Nanopore ◽

Long Read ◽

Read Error Correction

Abstract Background Long read sequencing technologies such as Oxford Nanopore can greatly decrease the complexity of de novo genome assembly and large structural variation identification. Currently Nanopore reads have high error rates, and the errors often cluster into low-quality segments within the reads. The limited sensitivity of existing read-based error correction methods can cause large-scale mis-assemblies in the assembled genomes, motivating further innovation in this area. Results Here we developed a Convolutional Neural Network (CNN) based method, called MiniScrub, for identification and subsequent “scrubbing” (removal) of low-quality Nanopore read segments to minimize their interference in downstream assembly process. MiniScrub first generates read-to-read overlaps via MiniMap2, then encodes the overlaps into images, and finally builds CNN models to predict low-quality segments. Applying MiniScrub to real world control datasets under several different parameters, we show that it robustly improves read quality, and improves read error correction in the metagenome setting. Compared to raw reads, de novo genome assembly with scrubbed reads produces many fewer mis-assemblies and large indel errors. Conclusions MiniScrub is able to robustly improve read quality of Oxford Nanopore reads, especially in the metagenome setting, making it useful for downstream applications such as de novo assembly. We propose MiniScrub as a tool for preprocessing Nanopore reads for downstream analyses. MiniScrub is open-source software and is available at https://bitbucket.org/berkeleylab/jgi-miniscrub.

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A long reads-based de-novo assembly of the genome of the Arlee homozygous line reveals chromosomal rearrangements in rainbow trout

G3 Genes|Genome|Genetics ◽

10.1093/g3journal/jkab052 ◽

2021 ◽

Author(s):

Guangtu Gao ◽

Susana Magadan ◽

Geoffrey C Waldbieser ◽

Ramey C Youngblood ◽

Paul A Wheeler ◽

...

Keyword(s):

Rainbow Trout ◽

Chromosome Number ◽

Genome Assembly ◽

De Novo Assembly ◽

De Novo ◽

Sequence Data ◽

Structural Variations ◽

High Coverage ◽

Haploid Chromosome Number ◽

Long Reads

Abstract Currently, there is still a need to improve the contiguity of the rainbow trout reference genome and to use multiple genetic backgrounds that will represent the genetic diversity of this species. The Arlee doubled haploid line was originated from a domesticated hatchery strain that was originally collected from the northern California coast. The Canu pipeline was used to generate the Arlee line genome de-novo assembly from high coverage PacBio long-reads sequence data. The assembly was further improved with Bionano optical maps and Hi-C proximity ligation sequence data to generate 32 major scaffolds corresponding to the karyotype of the Arlee line (2 N = 64). It is composed of 938 scaffolds with N50 of 39.16 Mb and a total length of 2.33 Gb, of which ∼95% was in 32 chromosome sequences with only 438 gaps between contigs and scaffolds. In rainbow trout the haploid chromosome number can vary from 29 to 32. In the Arlee karyotype the haploid chromosome number is 32 because chromosomes Omy04, 14 and 25 are divided into six acrocentric chromosomes. Additional structural variations that were identified in the Arlee genome included the major inversions on chromosomes Omy05 and Omy20 and additional 15 smaller inversions that will require further validation. This is also the first rainbow trout genome assembly that includes a scaffold with the sex-determination gene (sdY) in the chromosome Y sequence. The utility of this genome assembly is demonstrated through the improved annotation of the duplicated genome loci that harbor the IGH genes on chromosomes Omy12 and Omy13.

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